Keywords: Quantitative Imaging, Image Reconstruction
Motivation: Quantitative T1 (qT1) using MPnRAGE is a promising brain biomarker. However, reliable qT1 measurements at 1 mm isotropic resolution across the brain may require long scan times (>8min).
Goal(s): We aim to develop a low-rank denoising strategy providing reliable qT1 estimations from accelerated scans in about 2 minutes.
Approach: We developed a novel strategy using two U-Net models, the denoiser and T1-estimator, trained together to jointly convert accelerated low-rank scans into accurate qT1 maps.
Results: Our method exhibits good bias correction with low errors in both gray matter and white matter (<3%) with high image acceleration.
Impact: Our method provides fast and accurate whole-brain high-resolution qT1 estimation from MPnRAGE scans in about 2 minutes.
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